QUALITY OF SERVICE BASED WEB SERVICE SELECTION: AN EVALUATION OF TECHNIQUES

In service oriented computing, web services are the basic construct that aims to facilitate building of business application in a more flexible and interoperable manner for enterprise collaboration. One of the most promising advantages of web service technology is the possibility of creating added-value services by combining existing ones. A key step for composing and executing services lies in the selection of the individual services to use. Much attention has been devoted to appropriate selection of service functionalities, but also the non-functional properties of the services play a key role. A web service selection technique must take as much as possible the important influencing aspects into account to the selection processes in order to minimize the selection efforts. This paper evaluates several web service selection techniques published in literature with the focus on their contributions to web service selection. The evaluation results may be used as a basis for improving web service selection techniques that may simplify the selection tasks

Analyzing

Assessing the quality of external software before integrating it in to the project development is very challenging now days. As IT industry is moving towards newly evolving tool named SaaS(Software as a Service) , the risk of integrating the external software to the project development has been increased. Presently integration of external software is going on, but they use the trad itional way of collecting the feedbacks to identify whether to use that external software into the project or not, which may produce an unfair results at the end of project deployment. So in this perspective we are going to propose an automated framework to rate and select a service by identifying quality and reputation .And we mainly focused on addressing the risk in proposing external software by using quality and reputation of it

Assessing the Quality of a Software Service at the Time of Project Development by Identifying its Reputation

At the time of integration of the software while developing a project the reputation and the quality of execution is tough to identify and which is very risky. As the software industry is introduced with a new type of service delivery model known as SaaS(Software as a service),the problem has increased a lot . Existing system be inclined to rely on rating from customer to experiences of past service which may create major issues in terms of subjectivity and rating unfairness. Few previous works have been considered quality and reputation for selection of services bur none have done service rating process through automation. We proposed an automated quality and reputation framework for rating and selecting a service. In this paper the management of risk has been formulated in context of development of the project using third party software service components and credibility is calculated by a measured reputation system

A Framework for Trusted Services

An existing challenge when selecting services to be used in a service- based system is to be able to distinguish between good and bad services. In this paper we present a trust-based service selection framework. The framework uses a trust model that calculates the level of trust a user may have with a service based on past experience of the user with the service and feedback about the service received from other users. The model takes into account different levels of trust among users, different relationships between users, and different levels of importance that a user may have for certain quality aspects of a service. A prototype tool has been implemented to illustrate and evaluate the work. The trust model has been evaluated in terms of its capacity to adjust itself due to changes in user ratings and its robustness

Trust Model for Optimized Cloud Services

Cloud computing with its inherent advantages draws attention for business critical applications, but concurrently expects high level of trust in cloud service providers. Reputation-based trust is emerging as a good choice to model trust of cloud service providers based on available evidence. Many existing reputation based systems either ignore or give less importance to uncertainty linked with the evidence. In this paper, we propose an uncertainty model and define our approach to compute opinion for cloud service providers. Using subjective logic operators along with the computed opinion values, we propose mechanisms to calculate the reputation of cloud service providers. We evaluate and compare our proposed model with existing reputation models

A trust based methodology for web service selection

In this paper, we propose a methodology for addressing trust in Semantic Web Services (SWS) - based applications. The aim is to enhance the capability-driven selection provided by current SWS frameworks with the introduction of trust-based selection criteria. We present an ontology - Web Services Trust Ontology (WSTO) - that models the context of a trust-based interaction and enables the participants to describe semantically their trust requirements and guarantees. WSTO makes use of WSMO as reference ontology for representing Web Services and embodies the problem of finding the most "trusted" Web service as a classification problem. To test our methodology, we implemented a specific module within IRS-III - a WSMO-based SWS broker - and deployed a prototype application based on a use case scenario

A formal model for classifying trusted Semantic Web Services

Semantic Web Services (SWS) aim to alleviate Web service limitations, by combining Web service technologies with the potential of Semantic Web. Several open issues have to be tackled yet, in order to enable a safe and efficient Web services selection. One of them is represented by trust. In this paper, we introduce a trust definition and formalize a model for managing trust in SWS. The model approaches the selection of trusted Web services as a classification problem, and it is realized by an ontology, which extends WSMO. A prototype is deployed, in order to give a proof of concept of our approach

Workload patterns for quality-driven dynamic cloud service configuration and auto-scaling

Cloud service providers negotiate SLAs for customer services they offer based on the reliability of performance and availability of their lower-level platform infrastructure. While availability management is more mature, performance management is less reliable. In order to support an iterative approach that supports the initial static infrastructure configuration as well as dynamic reconfiguration and auto-scaling, an accurate and efficient solution is required. We propose a prediction-based technique that combines a pattern matching approach with a traditional collaborative filtering solution to meet the accuracy and efficiency requirements. Service workload patterns abstract common infrastructure workloads from monitoring logs and act as a part of a first-stage high-performant configuration mechanism before more complex traditional methods are considered. This enhances current reactive rule-based scalability approaches and basic prediction techniques based on for example exponential smoothing